Open AccessClassification Airbrone LiDAR Point cloud Data
Author(s) -
Naga Madhavi lavanya Gandi
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst0701008
Subject(s) - lidar , remote sensing , point cloud , land cover , ranging , cohen's kappa , rgb color model , computer science , contextual image classification , cloud cover , image resolution , environmental science , cloud computing , artificial intelligence , geography , land use , machine learning , engineering , telecommunications , civil engineering , image (mathematics) , operating system
Land cover classification information plays a very important role in various applications. Airborne Lightdetection and Ranging (LiDAR) data is widely used in remote sensing application for the classification of landcover. The present study presents a Spatial classification method using Terrasoild macros . The data usedin this study are a LiDAR point cloud data with the wavelength of green:532nm, near infrared:1064nm andmid-infrared-1550nm and High Resolution RGB data. The classification is carried in TERRASCAN Modulewith twelve land cover classes. The classification accuracies were assessed using high resolution RGB data.From the results it is concluded that the LiDAR data classification with overall accuracy and kappa coefficient85.2% and 0.7562.